The goal of the MENTOR project is to implement and begin evaluation of a computer-based methodology for reducing therapeutic misadventures. The project will use principles of artificial intelligence to create an on-line expert system to continuously monitor the drug therapy of individual patients and generate specific warnings of potential and/or actual unintended effects of therapy. The appropriate patient information will be automatically acquired through interfaces to a hospital information system. This data will be monitored by a system that is capable of employing complex chains of reasoning to evaluate therapeutic decisions and arrive at valid conclusions in the context of all information available on the patient. The results reached by the system will be fed back to the responsible physicians to assist future decision making. Specific objectives of this proposal include: 1. Implement a prototype computer-based expert system to continuously monitor in-patient drug therapy. It will use a modular medical knowledge base and a separate inference engine to apply the knowledge to specific situations. 2. Select a small number of important and frequently occurring drug therapy problems that can lead to therapeutic misadventures and construct a comprehensive knowledge base necessary to detect these situations. 3. Select and test several methods of formulating and providing warnings to physicians in order to implement a feedback method that is acceptable and useful. 4. Design and begin implementation of an evaluation of the prototype MENTOR system with respect to its impact on the physicians therapeutic decision making as well as its effects on the patient in terms of specific mortality and morbidity measures. The work in the proposed project will build on the extensive previous work in drug monitoring done by these investigators in the Division of Clinical Pharmacology at Stanford and at the University of Maryland School of Pharmacy.